Medical treatment of acromegaly is currently performed through a trial-error approach using first generation somatostatin receptor ligands (fgSRLs) as first-line drugs, with an effectiveness of about 50%, and subsequent drugs are indicated through clinical judgment. Some biomarkers can predict fgSRLs response. Here we report the results of the ACROFAST study, a clinical trial in which a protocol based on predictive biomarkers of fgSRLs was evaluated.
METHODS: prospective trial (21 university hospitals) comparing the effectiveness and time-to control of two treatment protocols during 12 months: A) A personalized protocol in which first option were fgSRLs as monotherapy or in combination with pegvisomant or, pegvisomant as monotherapy depending on the short Acute Octreotide Test (sAOT) results, tumor T2 Magnetic Resonance (MRI) signal or immunostaining for E-cadherin and, B) A control group with treatment always started by fgSRLs and the other drugs included after demonstrating inadequate control.
RESULTS: Eighty-five patients participated; 45 in the personalized and 40 in the control group. More patients in the personalized protocol achieved hormonal control compared to those in the control group (78% vs 53%, p < 0.05). Survival analysis revealed a hazard ratio for achieving hormonal control adjusted by age and sex of 2.53 (CI 1.30-4.80). Patients from personalized arm were controlled in a shorter period of time (p = 0.01).
CONCLUSIONS: Personalized medicine is feasible using a relatively simple protocol and allows a higher number of patients achieving control in a shorter period of time.

Although predictors of response to first-generation somatostatin receptor ligands (fg-SRLs), and to a lesser extent to pasireotide, have been studied in acromegaly for many years, their use is still not recommended in clinical guidelines. Is there insufficient evidence to use them? Numerous biomarkers including various clinical, functional, radiological and molecular markers have been identified. The first ones are applicable pre-surgery, while the molecular predictors are utilized for patients not cured after surgery. In this regard, factors predicting a good response to fg-SRLs are specifically: low basal GH, a low GH nadir in the acute octreotide test, T2 MRI hypointensity, a densely granulated pattern, high immunohistochemistry staining for somatostatin receptor 2 (SSTR2), and E-cadherin. However, there is still a lack of consensus regarding which of these biomarkers is more useful or how to integrate them into clinical practice. With classical statistical methods, it is complex to define reliable and generalizable cut-off values for a single biomarker. The potential solution to the limitations of traditional methods involves combining systems biology with artificial intelligence, which is currently providing answers to such long-standing questions that may eventually be finally included into the clinical guidelines and make personalized medicine a reality. The aim of this review is to describe the current knowledge of the main fg-SRLs and pasireotide response predictors, discuss their current usefulness, and point to future directions in the research of this field.